@inproceedings{daume13hrtf,
  title     = {Kernel  Regression for Head-Related Transfer Function Interpolation and Spectral Extrema Extraction},
  author    = {Yuancheng Luo and Dmitry N. Zotkin and Hal {Daum\'e III} and Ramani Duraiswami},
  booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year      = {2013},
  abstract  = {
    Head-Related Transfer Function (HRTF) representation and interpolation is an important problem in spatial audio. We present a kernel regression method based on Gaussian process (GP) modeling
    of the joint spatial-frequency relationship between HRTF measurements and obtain a smooth non-linear representation based on data
    measured over both arbitrary and structured spherical measurement
    grids. This representation is further extended to the problem of extracting spectral extrema (notches and peaks). We perform HRTF
    interpolation and spectral extrema extraction using freely available
    CIPIC HRTF data. Experimental results are shown.
  },
  keywords  = {ml},
  url       = {http://pub.hal3.name/#daume13hrtf},
}